Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins
The Internet of Things (IoT) has brought about significant transformations in multiple sectors, including healthcare and navigation systems, by offering essential functionalities crucial for their operations. Nevertheless, there is ongoing debate surrounding the unexplored possibilities of the IoT w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/24/9656 |
| _version_ | 1797379430939623424 |
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| author | Faiza Qayyum Reem Alkanhel Ammar Muthanna |
| author_facet | Faiza Qayyum Reem Alkanhel Ammar Muthanna |
| author_sort | Faiza Qayyum |
| collection | DOAJ |
| description | The Internet of Things (IoT) has brought about significant transformations in multiple sectors, including healthcare and navigation systems, by offering essential functionalities crucial for their operations. Nevertheless, there is ongoing debate surrounding the unexplored possibilities of the IoT within the energy industry. The requirement to better the performance of distributed energy systems necessitates transitioning from traditional mission-critical electric smart grid systems to digital twin-based IoT frameworks. Energy storage systems (ESSs) used within nano-grids have the potential to enhance energy utilization, fortify resilience, and promote sustainable practices by effectively storing surplus energy. The present study introduces a conceptual framework consisting of two fundamental modules: (1) Power optimization of energy storage systems (ESSs) in peer-to-peer (P2P) energy trading. (2) Task orchestration in IoT-enabled environments using digital twin technology. The optimization of energy storage systems (ESSs) aims to effectively manage surplus ESS energy by employing particle swarm optimization (PSO) techniques. This approach is designed to fulfill the energy needs of the ESS itself as well as meet the specific requirements of participating nano-grids. The primary objective of the IoT task orchestration system, which is based on the concept of digital twins, is to enhance the process of peer-to-peer nano-grid energy trading. This is achieved by integrating virtual control mechanisms through orchestration technology combining task generation, device virtualization, task mapping, task scheduling, and task allocation and deployment. The nano-grid energy trading system’s architecture utilizes IoT sensors and Raspberry Pi-based edge technology to enable virtual operation. The evaluation of the proposed study is carried out through the examination of a simulated dataset derived from nano-grid dwellings. This research analyzes the efficacy of optimization approaches in mitigating energy trading costs and optimizing power utilization in energy storage systems (ESSs). The coordination of IoT devices is crucial in improving the system’s overall efficiency. |
| first_indexed | 2024-03-08T20:23:08Z |
| format | Article |
| id | doaj.art-7f1e7dedc1d14523914b67766d608c9f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T20:23:08Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-7f1e7dedc1d14523914b67766d608c9f2023-12-22T14:40:06ZengMDPI AGSensors1424-82202023-12-012324965610.3390/s23249656Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital TwinsFaiza Qayyum0Reem Alkanhel1Ammar Muthanna2Department of Computer Engineering, Jeju National University, Jeju-si 63243, Republic of KoreaDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi ArabiaDepartment of Telecommunication Systems, Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya, 117198 Moscow, RussiaThe Internet of Things (IoT) has brought about significant transformations in multiple sectors, including healthcare and navigation systems, by offering essential functionalities crucial for their operations. Nevertheless, there is ongoing debate surrounding the unexplored possibilities of the IoT within the energy industry. The requirement to better the performance of distributed energy systems necessitates transitioning from traditional mission-critical electric smart grid systems to digital twin-based IoT frameworks. Energy storage systems (ESSs) used within nano-grids have the potential to enhance energy utilization, fortify resilience, and promote sustainable practices by effectively storing surplus energy. The present study introduces a conceptual framework consisting of two fundamental modules: (1) Power optimization of energy storage systems (ESSs) in peer-to-peer (P2P) energy trading. (2) Task orchestration in IoT-enabled environments using digital twin technology. The optimization of energy storage systems (ESSs) aims to effectively manage surplus ESS energy by employing particle swarm optimization (PSO) techniques. This approach is designed to fulfill the energy needs of the ESS itself as well as meet the specific requirements of participating nano-grids. The primary objective of the IoT task orchestration system, which is based on the concept of digital twins, is to enhance the process of peer-to-peer nano-grid energy trading. This is achieved by integrating virtual control mechanisms through orchestration technology combining task generation, device virtualization, task mapping, task scheduling, and task allocation and deployment. The nano-grid energy trading system’s architecture utilizes IoT sensors and Raspberry Pi-based edge technology to enable virtual operation. The evaluation of the proposed study is carried out through the examination of a simulated dataset derived from nano-grid dwellings. This research analyzes the efficacy of optimization approaches in mitigating energy trading costs and optimizing power utilization in energy storage systems (ESSs). The coordination of IoT devices is crucial in improving the system’s overall efficiency.https://www.mdpi.com/1424-8220/23/24/9656Internet of Thingscomplex problem solvingcritical IoT systemsnano-gridoptimizationtask modeling |
| spellingShingle | Faiza Qayyum Reem Alkanhel Ammar Muthanna Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins Sensors Internet of Things complex problem solving critical IoT systems nano-grid optimization task modeling |
| title | Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins |
| title_full | Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins |
| title_fullStr | Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins |
| title_full_unstemmed | Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins |
| title_short | Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins |
| title_sort | maximizing efficiency in energy trading operations through iot integrated digital twins |
| topic | Internet of Things complex problem solving critical IoT systems nano-grid optimization task modeling |
| url | https://www.mdpi.com/1424-8220/23/24/9656 |
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